FEQA: A Question Answering Evaluation Framework for Faithfulness
Assessment in Abstractive Summarization

FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization

7 May 2020

Esin Durmus

Papers citing "FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization"

9 / 109 papers shown

Title
Evaluating Factuality in Generation with Dependency-level Entailment Tanya Goyal Greg Durrett 23 147 0 12 Oct 2020
CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems Yiran Chen Pengfei Liu Ming Zhong Zi-Yi Dou Danqing Wang Xipeng Qiu Xuanjing Huang ELM 27 24 0 11 Oct 2020
Multi-Fact Correction in Abstractive Text Summarization Yue Dong Shuohang Wang Zhe Gan Yu Cheng Jackie C.K. Cheung Jingjing Liu KELM HILM 15 118 0 06 Oct 2020
Extracting Summary Knowledge Graphs from Long Documents Zeqiu Wu Rik Koncel-Kedziorski Mari Ostendorf Hannaneh Hajishirzi 35 15 0 19 Sep 2020
SummEval: Re-evaluating Summarization Evaluation Alexander R. Fabbri Wojciech Kry'sciñski Bryan McCann Caiming Xiong R. Socher Dragomir R. Radev HILM 38 689 0 24 Jul 2020
Evaluation of Text Generation: A Survey Asli Celikyilmaz Elizabeth Clark Jianfeng Gao ELM LM&MA 19 376 0 26 Jun 2020
Enhancing Factual Consistency of Abstractive Summarization Chenguang Zhu William Fu-Hinthorn Ruochen Xu Qingkai Zeng Michael Zeng Xuedong Huang Meng Jiang HILM KELM 193 40 0 19 Mar 2020
Text Summarization with Pretrained Encoders Yang Liu Mirella Lapata MILM 258 1,433 0 22 Aug 2019
SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents Ramesh Nallapati Feifei Zhai Bowen Zhou 207 1,255 0 14 Nov 2016